The Transportation Systems Sector is one of the sixteen critical infrastructure sectors identified by the Cybersecurity and Infrastructure Security Agency (CISA) and plays a crucial role in ensuring public safety, economic stability, and national security. The Massachusetts Bay Transportation Authority (MBTA) serves as the primary public transportation system in the Greater Boston Area, with the Green Line representing one of the oldest and most complex rapid transit systems in the network. This paper presents a network-based risk and resilience assessment of the MBTA Green Line using graph theory, network metrics, and the Model-Based Risk Analysis (MBRA) tool. The original 70-station Green Line network is simplified into a 17-node model, and key metrics, including degree centrality, betweenness centrality, eigenvector centrality, spectral radius, node robustness, and blocking nodes, are computed using Python-based analysis. Critical vulnerability is derived using the MBRA resiliency equation, and random, targeted, and cyber-physical attack scenarios are evaluated. The results identify North Station, Government Center, Haymarket, Copley, and Kenmore as the most critical nodes. A fault tree analysis between Kenmore and Copley further demonstrates the impact of budget allocation on threat reduction. This work highlights key vulnerabilities in the Green Line network and provides actionable recommendations to improve resilience against cyber-physical threats.
翻译:交通系统部门是美国网络安全与基础设施安全局(CISA)认定的十六个关键基础设施部门之一,在保障公共安全、经济稳定和国家安全方面发挥着至关重要的作用。马萨诸塞湾交通管理局(MBTA)是大波士顿地区的主要公共交通系统,其中绿线是该网络中历史最悠久、结构最复杂的快速交通系统之一。本文基于图论、网络度量指标及基于模型的风险分析(MBRA)工具,对MBTA绿线进行了网络化的风险与韧性评估。原始的70站点绿线网络被简化为一个17节点模型,并通过基于Python的分析计算了关键度量指标,包括度中心性、介数中心性、特征向量中心性、谱半径、节点鲁棒性及阻塞节点。利用MBRA韧性方程推导出关键脆弱性,并评估了随机攻击、针对性攻击及网络-物理攻击场景。结果表明,北站、政府中心、海马克特、科普利及肯莫尔为最关键节点。在肯莫尔与科普利之间进行的故障树分析进一步揭示了预算分配对威胁消减的影响。本研究揭示了绿线网络的关键脆弱点,并为提升应对网络-物理威胁的韧性提供了可操作的改进建议。